Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization
Fan Yang,Wenxuan Zhou,Zuxin Liu,Ding Zhao,David Held,Fan Yang,Wenxuan Zhou,Zuxin Liu,Ding Zhao,David Held
Safe Reinforcement Learning (RL) plays an important role in applying RL algorithms to safety-critical real-world applications, addressing the trade-off between maximizing rewards and adhering to safety constraints. This work introduces a novel approach that combines RL with trajectory optimization to manage this trade-off effectively. Our approach embeds safety constraints within the action space ...
